Digital Commons Network^™

Insider Threat: A Case Study Of The Maroochy Water Services Attack, Samuel Rector

Cybersecurity Undergraduate Research Showcase

In 2000, a former employee at Hunter Watertech went rogue and caused a spill of 800,000 liters of sewage. He leveraged his insider knowledge and access to stolen equipment in order to seek retribution for the company that wronged him. After three months of torment police arrested him and an investigation and many studies were done on the incident. A consensus remains that much of this chaos was preventable with simple cybersecurity implementations.

Game Hacking & Anti-Cheat Analysis, Quang Hoang

Cybersecurity Undergraduate Research Showcase

Reverse engineering and analyzing game hacking and anti-cheat mechanisms is a complex and evolving field. This research document explores the history of game hacking, various techniques used in game hacking, and the countermeasures implemented by anti-cheat systems. Through case studies, we illustrate the strategies involved in creating cheats. Specifically, we demonstrate how to hack the open-source game AssaultCube using memory editing and code injection techniques available in Cheat Engine in a step-by-step manner so that the reader can theoretically reproduce the results shown in this paper. We also dissect the game’s anti-cheat mechanisms, identifying their strengths and weaknesses. This document …

A Scalable Cybersecurity Model For Academic Makerspaces, William Faircloth

Cybersecurity Undergraduate Research Showcase

Academic makerspaces have become integral hubs of innovation on university campuses, providing students with access to industrial-grade operational technology (OT) such as 3D printers and CNC machines. However, the security posture for these spaces has overwhelmingly focused on physical safety, creating a significant cybersecurity gap. This oversight leaves networked OT vulnerable to cyberattacks, which threaten student intellectual property, expensive equipment, and the integrity of the broader institutional network. This research addresses this critical vulnerability by developing and implementing a secure and scalable cybersecurity model at the Old Dominion University Computer Science Makerspace, founded on two core principles: robust network segmentation …

Deconstructing Tycoon 2fa: A Static Analysis Approach To Threat Intelligence And Automated Defense, Daniel A. Austin Jr

Cybersecurity Undergraduate Research Showcase

It's gotten much easier to be a cybercriminal. We're seeing a boom in "Phishing-as-a-Service" (PaaS) platforms, which sell advanced phishing attacks as a ready-to-use product. This means almost anyone can now get the tools to launch sophisticated attacks, even if they don't have a lot of technical skill.

This research dives into one of the most prominent threats, the Tycoon 2FA phishing kit. This kit is dangerous because it's designed to bypass Multi-Factor Authentication (MFA) using what is known as an Adversary-in-the-Middle (AiTM) attack.

This paper covers how I built and tested a set of Python-based tools to perform "static …

Securitizing Kinmen: China’S Gray Zone Strategy And The Evolution Of The Kinmen Model, Ian Murphy

Political Science & Geography Faculty Publications

This paper examines the evolving dynamics of cross-strait relations through the lens of securitization theory, focusing on China’s strategic deployment of what it calls the Kinmen Model and its implications for regional security. While existing discourse predominantly concentrates on a potential full-scale invasion of Taiwan, this study shifts attention to the strategic significance of the outlying islands and the nuanced employment of securitization to exert indirect control. Utilizing Vuori’s (2008) framework for analyzing securitization in non-democratic contexts, this research conducts a discourse analysis of nineteen Chinese language media sources to dissect the speech acts employed by Chinese media and their …

Detecting Generative-Ai-Enabled Polymorphic Malware: A Semantic-Behavior Approach, Allyson M. Morris

Cybersecurity Undergraduate Research Showcase

AI drastically reduces the effort required to produce malware that mutates both its code and behavior, thereby creating polymorphic and nondeterministic variants in which traditional signatures and many heuristic defenses fail. In this paper, I survey recent developments in AI-assisted malware generation, explain why conventional defenses are insufficient, and propose a layered detection architecture emphasizing semantic behavior, streaming anomaly detection, and defensive generative augmentation. I also outline why this approach generalizes to previously unseen AI-mutated samples, provide an evaluation plan with meaningful metrics, and describe a feasible MVP roadmap for practical deployment. Recent disclosures and threat intelligence further highlight the …

A Systematic Review Of Poisoning Attacks Against Large Language Models (Llm), Patrick Mcguffin

Cybersecurity Undergraduate Research Showcase

This paper provides a comprehensive review of poisoning attacks against large language models (LLMs), drawing primarily from Fendley et al. (2025) and complementary studies from 2022–2025. It categorizes poisoning research into two key dimensions, Metrics and Specifications, to evaluate how attack success is measured and how attacks are implemented. This paper synthesizes quantitative results, experimental findings, and defense strategies across data, model, and multi-modal poisoning contexts. Finally, it highlights emerging challenges posed by self-adaptive and synthetic-data-driven LLMs, and proposes future research directions to strengthen model security and reliability.

A Comprehensive Evaluation Of Next-Generation Firewall Effectiveness Against Encrypted And Evasive Threats In Enterprise Networks, John Costanzo, Favour Anene

Cybersecurity Undergraduate Research Showcase

Encrypted traffic is becoming a pillar of security and privacy in enterprise networks. According to Google Transparency Report, over 95 percent of internet traffic is encrypted with the use of Hypertext Transfer Protocol secure (HTTPS), Transport Layer Security (TLS) 1.3 and Quick UDP Internet Connections (QUIC). Although encryption safeguards confidentiality and integrity, it has also introduced new blind spots to the conventional security solutions. Encrypted channels are used to hide command-and-control (C2) traffic, issue malware and extract sensitive data without their notice.

To make the issue even harder, the opponents have sophisticated avoidance methods including traffic fragmentation, tunneling, and polymorphic …

Investigating The Security Vulnerabilities Of Ip Cameras: Classifications And Trends From Public Cve Data, Sam Oliver

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) devices are increasingly targeted by cyber attacks due to weak authentication, insecure communication protocols, outdated firmware, and many other vulnerabilities. Internet Protocol (IP) cameras, a subset of these IoT devices, are particularly vulnerable and often transmit sensitive information. This paper analyzes vulnerability data from the National Vulnerability Database (NVD) to classify security vulnerabilities affecting IP cameras. Using this dataset, the paper examines the types and frequencies of these vulnerabilities, including authentication bypass, web interface exploits, and default and weak credentials. We additionally examine trends over time and across categories. This research aims to identify the primary …

2025 Conference Program, Gpis Department, Old Dominion University

Graduate Research Conference (GSIS)

Schedule for ODU's 2025 Graduate Research Conference: Stormy Weather: Pressing Issues in International Politics

Attributes Of Artificial Wetlands Colonized By Ambystoma Maculatum On A Virginia Surface Mine, Hunter Hill, Garrett Stiltner, Walter H. Smith

Virginia Journal of Science

Landscapes impacted by surface mineral extraction present a range of artificial wetland habitats potentially useable by pool-breeding amphibians, although little information exists in the literature detailing which attributes influence breeding site selection by wetland amphibian specialists in post-mined landscapes. We compared attributes of artificial wetlands consistently used and unused as oviposition sites by Spotted Salamanders (Ambystoma maculatum) over a six-year period on a 120-ha former surface mine in Wise County, Virginia, USA. Salamanders non-randomly selected wetlands as oviposition sites, with one-third of available wetlands within the study area showing evidence of ovipositioning. Wetlands used as breeding sites were …

Review Of How To Win Environmental Victories, By Richard S. Groover, Phd, Shalini Upadhyaya

Virginia Journal of Science

Book Review:

Groover, Richard S. 2025. How to Win Environmental Victories. Nighthawk Publication, 116 pp.

Information & Schedule Flyer, Macon & Joan Brock Virginia Health Sciences At Old Dominion University

Cardiovascular Research Symposium

Information and schedule for Cardiovascular Research Symposium: Bridging Gaps and Advancing Care.

Mechanical Circulatory Support As A Bridge To Early Recovery Of Left Ventricular Function In Fulminant Myocarditis, Juan Munoz-Moreno, Gina Sanchez, Johanna Contreras

Cardiovascular Research Symposium

Background: Fulminant myocarditis (FM) is a rare cause of acute heart failure that can lead to a rapid left ventricular ejection fraction (LVEF) decline within four weeks. With in-hospital mortality up to 18.2%, timely mechanical circulatory support (MCS) is essential to stabilize hemodynamics and bridge to recovery or transplantation.

Case: A 49-year-old Japanese man with hypertension and diabetes presented with two weeks of dyspnea and angina after a flu-like illness. On admission, he developed ventricular fibrillation requiring advanced CPR. Physical exam revealed pulmonary congestion. ECG showed repolarization abnormalities. TTE demonstrated severe biventricular dysfunction (LVEF 9%, RVFAC 9%). Labs showed elevated …

Sociohydrodynamics: Data-Driven Modeling Of Social Behavior, Daniel S. Seara, Jonathan Colen, Michel Fruchart, Yael Avni, David G. Martin, Vincenzo Vitelli

Data Science Faculty Publications

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard …

Palliative Inotropic Support In A Patient With End-Stage Systolic Heart Failure, Christiana King, Justin Hayes

Cardiovascular Research Symposium

No abstract provided.

"Lost To Follow Up:" A Case Of An Adult Congenital Heart Defect Patient Who Faced Morbidity In Adulthood After Lacking Transitional Care Following Medical Intervention In Childhood, Mackenzie Kelley, Ashish Saini

Cardiovascular Research Symposium

CASE PRESENTATION: This patient is a 40 y.o. male with a BMI of 46.2 kg/m2 who presented to the ED with fluid overload, shortness of breath, and orthopnea. The patient was tachycardic and physical exam revealed anasarca and ascites. The patient reported chronic lower extremity and scrotal edema so severe that he had been unable to walk and was mainly homebound for the past two years. The patient’s past medical history was significant for hypertension, alcohol use disorder with history of withdrawal, and a cardiac murmur which the patient attributed to a “hole in the heart” for which he had …

Association Of Physical Activity And Neighborhood Deprivation With Extracellular Vesicle Characteristics In African American Women With Obesity, Anca D. Dobrian, Yvonne Baumer, Tiffany Powell-Wiley, Lizzy Aquino-Peterson, Noel Miller

Cardiovascular Research Symposium

Association of Physical Activity and Neighborhood Deprivation with Extracellular Vesicle Characteristics in African American Women with Obesity

A Modern Analytical Method To Forecast Cerebrovascular Diseases (Cd), And Heart Diseases (Hd) Using Multivariate Time Series Model Utilizing The Cdc Provisional Mortality Data, Aditya Chakraborty, Mohan Pant

Cardiovascular Research Symposium

Background: In this study, a new analytical approach was introduced to answer specific questions related to mortalities due to cerebrovascular diseases, heart diseases, and the association of these mortalities with twelve other causes of death (COD).

Methods: A multivariate time series forecasting model was developed utilizing each of the CODs by taking the weekly and yearly seasonality into account, and the mortality counts were forecasted using the most recent CDC weekly mortality count data. A new COD data matrix was structured for all CODs as a function of weeks by combining the observed and predicted values of the mortality counts. …

How Are Teachers Leading Now? From Access To Activism: An Introduction To The Special Issue, Kaavonia Hinton, Jori S. Beck

Teaching & Learning Faculty Publications

In this introduction to a special issue on teacher leadership (TL), the editors argue that recent attacks against antiracist teaching have influenced TL. Thus, we offer an overview of several issues these collected authors explore related to TL, including access to TL for teachers of color; advancing equity through leadership teams; self-care for teacher advocates; and TL as advocacy, activism, and antiracist work.

Ai-Enhanced Structured Literacy Intervention For Secondary Students: A Case Study Of Science Of Reading, Jennifer Bird

Teaching & Learning Faculty Publications

This study examines the effectiveness of Lexia PowerUp, an AI-powered literacy program, for sixth-grade students requiring Tier 3 reading intervention. Seven sixth-grade students (six boys, one girl; five African American, two Caucasian; all qualifying for free/reduced lunch) participated in a six-month intervention combining 50 minutes of daily small-group instruction with individualized Lexia PowerUp usage. Researchers measured progress through Achieve 3000 Lexile assessments and Lexia PowerUp performance data across three skill strands: Word Study, Grammar, and Comprehension. All participants demonstrated Lexile level improvements from beginning-of-year to mid-year assessments, though students remained below sixth-grade benchmarks (925-1070L). Analysis of Lexia PowerUp progression showed …

Empathetic Differentiated Instruction In Deaf Education: Examining Influencing Factors And Experienced Educator Practices, Laura A. Blackburn

STEMPS Master's Level Projects and Papers

This mixed-methods study investigated how experienced K–12 deaf educators implement empathetic, differentiated instruction (EDI) to support the academic and linguistic needs of deaf students who use American Sign Language (ASL) as their language of learning. Guided by Tracey and Baaki’s instructional design empathy model and grounded in constructivism, the study explored how teachers navigated the tension between standardized, English (sound-based) curriculum demands and the need to make instructional decisions aligned with signed language modalities and responsive to students’ real-time learning needs.

A custom electronic survey was distributed to a national sample of experienced educators, with 19 respondents completing Likert-scale items, …

Adolescent E-Cigarette Expectancies: Measure Development And Preliminary Validity Of The Electronic Nicotine Vaping Outcomes Measure For Youth, Paul T. Harrell, Kelli J. England, Tracey E. Barnett, Vani N. Simmons, Richard W. Handel, Amy C. Paulson

Department of Pediatrics Faculty Publications

BACKGROUND: Electronic nicotine delivery systems (“e-cigarettes”) are the nicotine product most commonly used by adolescents. Research, treatment, and policy could benefit from measures of adolescent e-cigarette beliefs about outcomes of use (ie, expectancies). In the current study, we developed and tested an adolescent electronic nicotine vaping expectancy measure.

METHODS: A focus group with adolescents evaluated potential e-cigarette expectancy items. A panel of national experts assisted in revision of these items. Finally, items were administered to a sample of adolescents 14-17 years old (N = 267, Mean age 15.6, SD = 1.1, 50.9% Female, 50.2% Non-Hispanic White, 22.5% Non-Hispanic Black, 14.2% …

Intersecting Realities And Evolving Landscapes: Mapping Generative Ai Within The Framework Of Digital Rhetoric, Joshua Troy Nieubuurt

English Theses & Dissertations

The increased usage of [Generative] AI technologies (GenAI) in the 21st century has called into the question the rhetorical agency of these digital things. [Gen]AI has historically been framed within a Heideggerian “readiness-to-hand” dynamic in which it has been unilaterally conceived as a tool to be used by humans. This dissertation proposes that the GenAI assemblage is capable of being a co-actor in rhetorical spaces. To provide evidence for this stance This dissertation utilizes Actor Network Theory to map the actants within a GenAI assemblage. In doing so it allows for an understanding of the stakeholders (both human and non-human) …

Graduate Students’ Perspectives On Universal Design For Learning (Udl) 3.0 Guidelines: A Q-Methodology Study, Taylor C. Rodriguez

Educational Leadership & Workforce Development Theses & Dissertations

The purpose of this study was to explore graduate students’ perspectives of Q-methodology to understand their insights on the newly updated Universal Design for Learning (UDL) 3.0 guidelines and how they feel these guidelines support their academic journey. A Q-sort instrument consisting of 36 statements aligned with UDL 3.0 principles was administered to graduate students at the master’s and doctoral levels. Thirty-two participants completed the Q-sort activity, and factor analysis revealed four distinct viewpoints reflecting varied perceptions of UDL’s relevance and impact within graduate education.

Findings indicate areas of consensus among students, particularly regarding the importance of developing student autonomy …

Learning Regulatory Dna-Sequence Code Of Epigenetic Events Using Deep Neural Networks, Sanjeeva Reddy Dodlapati

Computer Science Theses & Dissertations

Epigenetic events, such as DNA methylation and histone modifications, arise from a complex interplay among genomic sequence, chromatin-remodeling factors, and environmental cues. These regulatory mechanisms can induce changes in gene expression without altering the underlying DNA sequence, playing critical roles in development, disease, and cellular differentiation. Among these events, DNA methylation is frequently profiled using bisulfite sequencing (e.g., whole-genome bisulfite sequencing [WGBS], reduced representation bisulfite sequencing [RRBS]). However, predictive modeling of epigenetic states—including methylation patterns and regulatory variant effects—remains challenging due to data sparsity, label noise, and limited uncertainty estimation in current deep learning approaches. This dissertation addresses these issues …

Examining Access, Outcomes, And The Experiences Of Black Women: Improving Racial Equity In Adult Drug Treatment Court, Laquana N. Askew

Sociology & Criminal Justice Theses & Dissertations

Black women face compounded systemic barriers in the criminal legal system because of oppression and erasure of their racial and gendered identities. Although Adult Drug Treatment Courts (DTCs) are designed to divert individuals with substance use disorders from incarceration with the alternative of therapeutic intervention, Black women, compared to their Black male and White female counterparts, remain underrepresented and experience less favorable outcomes despite their increased presence in the criminal legal system due to drug related offenses. Using an intersectional Black Feminist framework, the current study critically examines the processes and structural barriers that contribute to Black women’s limited access …

Multimedia Forensics: Identification And Verification Of Source Camera, Vehicle Speed Estimation, And Deepfakes Detection, Jiajun Jiang

Electrical & Computer Engineering Theses & Dissertations

This dissertation advances multimedia forensics by addressing three critical research areas that enhance the authenticity verification and analysis of digital media. Multimedia forensics, which encompasses techniques for examining images, videos, audio, and text, faces increasing challenges due to sophisticated editing tools and massive data volumes. In the first study, a fast source camera identification and verification method based on PRNU analysis is proposed for video forensic investigations. By integrating camera rolling and I-frame analysis, this approach achieves a processing speed improvement of at least 15 times over conventional frame-by-frame methods while reducing false positives. The second study focuses on vehicular …

Two Analytic Issues Arising From Models In Probability And Materials Science, Giang Vu Thanh Nguyen

Mathematics & Statistics Theses & Dissertations

This dissertation explores two distinct topics centered on mathematical models in probability theory and materials science. The first part investigates a series of functions derived from an adaptive algorithm designed to address the score-based secretary problem, a classic challenge in probability theory. This problem involves making immediate decisions to select the best candidate from a sequence of interviews. The algorithm aims to maximize the probability of selecting the optimal candidate based on observed scores. We prove two fundamental analytic properties of this sequence of functions as a theoretic support of the algorithm: first, the functions in the sequence each possess …

Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman

Electrical & Computer Engineering Theses & Dissertations

Processing multivariate time series signals collected from sensor networks is challenging because of complex temporal dependencies and non-stationarity. With the advent of artificial intelligence (AI) like machine learning and deep learning, it has become possible to process sensor-driven time series data more effectively than traditional statistical methods.

This dissertation aims to develop machine learning and deep learning models to address machine fault diagnosis using multivariate time series signals collected from the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The first goal of the proposed work is to develop deep learning–based classification models and an unsupervised fault clustering approach …